• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.58-58
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• 2022

With the development of advanced technology, automation of agricultural work is spreading. In association with the 4th industrial revolution-based technology, research on field smart farm technology is being actively conducted. A state-of-the-art unmanned automated agricultural production demonstration complex was established in Naju-si, Jeollanam-do. For the operation of the demonstration area platform, it is necessary to build a sophisticated, advanced, and intelligent field smart farming model. For the operation of the unmanned automated agricultural production demonstration area platform, we are building data on the growth of soybean for smart cultivated crops and conducting research to determine the optimal time for agricultural work. In order to operate an unmanned automation platform, data is collected to discover digital factors for water management immediately after planting, water management during the growing season, and determination of harvest time. A subsurface drip irrigation system was established for smart water management. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. Vegetation indices were collected using drones to find key factors in soybean production prediction. In addition, major growth characteristics such as stem length, number of branches, number of nodes on the main stem, leaf area index, and dry weight were investigated. By discovering digital factors for effective decision-making through data construction, it is expected to greatly enhance the efficiency of the operation of the unmanned automated agricultural production demonstration area.

• Korean Journal of Agricultural Science
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• v.46 no.2
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• pp.405-416
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• 2019

Weeds are a serious problem in crop production. Use of synthetic herbicides is rapidly increasing in weed management worldwide including Korea. Herbicide application reduces the time spent on weed control. However, the evolution of resistance to herbicides in weeds has become widespread as a natural response to selection pressure imposed by agricultural management activities. If an herbicide with the same mechanisms of action is used repeatedly and intensively, it can rapidly select for a weed biotype that shifts toward difficult-to-control becoming a more tolerant weed and lead to the evolution of herbicideresistant weeds. Moreover, agricultural and biological factors have an important role in the development of herbicide-resistant weed populations. Mitigating the evolution of herbicide resistance in weeds relies on reducing selection through the diversification of weed control techniques. The resistance management of weeds in the future will strongly depend on intensive cropping systems. The current situation of intensive cropping systems with their heavy reliance on the efficacy of chemical weed control will not lead to significant containment of this problem. Therefore, management strategies need to overcome the further spread of herbicide resistance in weeds in Korean crop production. This review presents the current information on herbicide resistance in Korea and factors controlling the development of herbicide resistant weeds.

• Smart Media Journal
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• v.12 no.10
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• pp.29-37
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• 2023

Human lifestyle is affected by the agricultural development in the last 12,000 years ago. The development of agriculture is one of the reasons that global population surged. To ensure sufficient food production for supporting human life, pesticides as a more effective and economical tools, are extensively used to enhance the yield quality and boost crop production. This study investigated the factors that affect crop production and whether the factors of pesticide usage are the most important factors in crop production using the dataset from Kaggle that provides information based on crops harvested by various farmers. Logistic regression is used to investigate the relationship between various factors and crop production. However, the logistic regression is unable to deal with predictors that are related to each other and identifying the greatest impact factor. Therefore, causal discovery is applied to address the above limitations. The result of causal discovery showed that crop condition is greatly impacted by the estimated insects count, where estimated insects count is affected by the factors of pesticide usage. This study enhances our understanding of the influence of pesticide usage on crop production and contributes to the progress of agricultural practices.

• Proceedings of the Korean Society of Crop Science Conference
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• 1995.05a
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• pp.10-11
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• 1995

• Journal of Agricultural Extension & Community Development
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• v.19 no.3
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• pp.699-727
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• 2012

Conditions of farm crop switching are affected by several important external factors such as agricultural products import opening, policy support, and climate change. Farming environment is always changing; barriers to imports are becoming lower and lower because of FTA and others, and climate change affects a boundary line of cultivation. Those situations give farmers motivation to change crops in order to cope with them. In addition, crop switching has been done in response to the local government measures about purchase of local agricultural products according to the local food and the expansion of organic agricultural products in school meal. Even though the favorable environment toward crop switching has been created, there are not many researches or outcomes regarding crop switching. Only few studies focus on the list of decision-making in crop switching, and locally suitable crop selection is not treated. In order to utilize crop switching as a farm management strategy, the proper frame should be studied and practical researches on application possibility also need. Therefore, study on crop switching is in a timely, proactive manner because farms catch the chance of expansion of school meal by changing crops. This paper applies HERO model used for venture foundation process to crop switching process. Success factors of HERO model are comprised of Habitate, Entrepreneurship, Resource, and Opportunity, and these phased application factors are applied to crop switching process. By doing so, each phase success factor of crop switching can be uncovered. Three farm organizations supplying organic agricultural products to schools are studied in Gyeonggi province. As a result, the stabilization stage cannot be achieved because of the habitate conditions and social conditions with low risk bearing of crop switching and current school meal systems are the main problems to block the diversification of risks. In order to succeed in crop switching, constructing the habitate in local districts or in systems of school meal is more effective than supporting each farm.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1586-1590
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• 2006

In order to calculate the actual erosion according to the universal soil loss equation (USLE) and to estimate the impact of land use on soil erosion in Saemangeum, it is important to know the C-factor. Based on the USLE crop-growth stages, the cover-management C-factors were calculated for the main crop and crop rotation systems by National Institute of Agricultural Science and Technology. Combining this result with statistical data about crop cultivation area and crop rotation systems, C-factors of each administrative district in Saemangeum watershed were calculated. The range of C-factors were between 0.28 and 0.35. High C-factor value was obtained with Gimje (C = 0.35) and small C-factor values were found in Wanju (C = 0.28) and Jeongeup (C = 0.29). With this result, calculated annual soil loss was 2,804,483 ton per year. Because of the lack of sufficient statistical data about crop rotation systems, further studies are required on collecting field survey data.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.126-126
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• 2022

Climate change has continued to impact meteorological factors like rainfall in many countries including Nigeria. Thus, altering the rainfall patterns which subsequently affect the crop yield. Maize is an important cereal grown in northern Nigeria, along with sorghum, rice, and millet. Due to the challenge of water scarcity during the dry season, it has become critical to design appropriate strategies for planning, developing, and management of the limited available water resources to increase the maize yield. This study, therefore, determines the quantity of water required to produce maize from planting to harvesting and the impact of drought on maize during different growth stages in the region. Rainfall data from six rain gauge stations for a period of 36 years (1979-2014) was considered for the analysis. The standardized precipitation and evapotranspiration index (SPEI) is used to evaluate the severity of drought. Using the CROPWAT model, the evapotranspiration was calculated using the Penman-Monteith method, while the crop water requirements (CWRs) and irrigation scheduling for the maize crop was also determined. Irrigation was considered for 100% of critical soil moisture loss. At different phases of maize crop growth, the model predicted daily and monthly crop water requirements. The crop water requirement was found to be 319.0 mm and the irrigation requirement was 15.5 mm. The CROPWAT 8.0 model adequately estimated the yield reduction caused by water stress and climatic impacts, which makes this model appropriate for determining the crop water requirements, irrigation planning, and management.

• Journal of Microbiology and Biotechnology
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• v.30 no.11
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• pp.1688-1696
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• 2020

Soil physical and chemical characteristics, soil potential denitrification rates (PDR), community composition and nirK-, nirS- and nosZ-encoding denitrifiers were studied by using MiSeq sequencing, quantitative polymerase chain reaction (qPCR), and terminal restriction fragment polymorphism (T-RFLP) technologies base on short-term (5-year) tillage field experiment. The experiment included four tillage treatments: conventional tillage with crop residue incorporation (CT), rotary tillage with crop residue incorporation (RT), no-tillage with crop residue retention (NT), and rotary tillage with crop residue removed as control (RTO). The results indicated that soil organic carbon, total nitrogen and NH₄⁺-N contents were increased with CT, RT and NT treatments. Compared with RTO treatment, the copies number of nirK, nirS and nosZ in paddy soil with CT, RT and NT treatments were significantly increased. The principal coordinate analysis indicated that tillage management and crop residue returning management were the most and the second important factors for the change of denitrifying bacteria community, respectively. Meanwhile, this study indicated that activity and community composition of denitrifiers with CT, RT and NT treatments were increased, compared with RTO treatment. This result showed that nirK, nirS and nosZ-type denitrifiers communities in crop residue applied soil had higher species diversity compared with crop residue removed soil, and denitrifying bacteria community composition were dominated by Gammaproteobacteria, Deltaproteobacteria, and Betaproteobacteria. Therefore, it is a beneficial practice to increase soil PDR level, abundance and community composition of nitrogen-functional soil microorganism by combined application of tillage with crop residue management.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2015.08a
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• pp.18-28
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• 2015

Apple is cultivated under various climatic conditions in many parts of the world. Better understanding of how climate, genotype, soil, and management factors interact to determine crop productivity will improve our ability to optimize crop selection, management strategies, and resource use efficiencies. We developed and applied a physiology-based apple canopy model to evaluate how climatic factors and crop phenotypes interact to determine biomass accumulation, radiation use efficiency (RUE), and water use efficiency (WUE) at multiple production sites between western and eastern states of the US including WA, CA, NY, WV, and PA. Our results indicate that solar radiation is a dominant factor limiting biomass production in the eastern states while VPD is the primary factor governing crop water use across eastern and western states during the peak growing season. Crop RUE and WUE were strongly correlated in the western states but not in the eastern states while VPD showed highly negative correlation with both RUE and WUE across all locations. The RUE improved with increasing fraction of diffuse radiation ($f_{df}$) and the $RUE-f_{df}$ relationships revealed distinctive responses between western and eastern states. Overall, the eastern locations exhibited slightly higher RUE and WUE than the western locations. However, overall productivity and total water use were greater in the western states. A clear decline of productivity with increasing temperature and afternoon VPD past an optimum was predicted in the western locations but this pattern was less clear in the eastern locations. We also discuss potential phenotypes with specific physiological and morphological traits that are differentially suitable for western and eastern locations. Our results provide plausible, spatially explicit explanations and insights to disentangle the complex relationships between crop productivity, resource use efficiencies, phenotype, and climate drivers in apple grown in the US.

• Journal of Environmental Science International
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• v.21 no.4
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• pp.461-470
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• 2012

Agriculture is more influenced by environmental factors rather than other industries. Among the environmental factors, the meteorological conditions mainly impact the output of agricultural products. Hence, the purpose of this study is to analyze the impact of meteorological factors on the output of elemental agricultural products. As a first step, we obtained the data of the meteorological factors (i.e., precipitation, humidity, temperature, insolation, snowdrifts, wind velocity) and the output of the various agricultural products (i.e., grain, fruits and vegetables, root crops, green vegetables, seasoned vegetables, fruits, special crops) from the year 1990 to 2009 (20 years) of Seoul and the six metropolitan cities in Korea. Then, the analysis of the correlation between the agricultural product with the largest output and the meteorological factors of the place where the corresponding agricultural product is most produced, was carried out in order to determine the core meteorological factor that most impacts the output of agricultural product. The correlation analysis revealed that humidity, insolation and wind velocity have been the crucial meteorological factors to influence the output of the agricultural products. From the result, we can induce that the meteorological forecast information about the vital meteorological factors, i.e., humidity, insolation and wind velocity, facilitates the optimized cultivation plan to maximize the output of agricultural products.